An In-depth Study of Bandwidth Allocation across Media Sources in Video Conferencing
Zejun Zhang, Xiao Zhu, Anlan Zhang, Feng Qian
Abstract
Video Conferencing Applications (VCAs) are indispensable for real-time communication in remote work and education by enabling simultaneous transmission of audio, video, and screen-sharing content. Despite their ubiquity, research on how these platforms allocate network bandwidth, especially under constrained conditions, and how these resource allocation strategies affect the users' Quality of Experience (QoE) is lacking. This paper addresses this gap by analyzing bandwidth allocation strategies in Zoom, Webex, and Google Meet, with a focus on QoE implications. To assess QoE, we propose a general QoE prediction model based on data collected from a study involving 800 participants. This study is a pioneering effort in evaluating multimedia transmissions across diverse scenarios and network conditions, advancing beyond prior research focused on single media types. The results demonstrate the model's effectiveness and generality in predicting QoE across various VCA scenarios.
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